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Record W2115243971 · doi:10.1098/rspb.2006.0435

Colour pattern as a single trait driving speciation in<i>Hypoplectrus</i>coral reef fishes?

2007· article· en· W2115243971 on OpenAlexaff
Oscar Puebla, Eldredge Bermingham, Frédéric Guichard, Elizabeth Whiteman

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsMcGill University
Fundersnot available
KeywordsDisruptive selectionAssortative matingBiologyParapatric speciationSympatric speciationEcological speciationGenetic algorithmSympatryCoral reef fishIncipient speciationEcologyCoral reefGene flowPomacentridaeTraitNatural selectionEvolutionary biologySelection (genetic algorithm)MatingGenetic variation

Abstract

fetched live from OpenAlex

Theory shows that speciation in the presence of gene flow occurs only under narrow conditions. One of the most favourable scenarios for speciation with gene flow is established when a single trait is both under disruptive natural selection and used to cue assortative mating. Here, we demonstrate the potential for a single trait, colour pattern, to drive incipient speciation in the genus Hypoplectrus (Serranidae), coral reef fishes known for their striking colour polymorphism. We provide data demonstrating that sympatric Hypoplectrus colour morphs mate assortatively and are genetically distinct. Furthermore, we identify ecological conditions conducive to disruptive selection on colour pattern by presenting behavioural evidence of aggressive mimicry, whereby predatory Hypoplectrus colour morphs mimic the colour patterns of non-predatory reef fish species to increase their success approaching and attacking prey. We propose that colour-based assortative mating, combined with disruptive selection on colour pattern, is driving speciation in Hypoplectrus coral reef fishes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.266

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.238
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations135
Published2007
Admission routes1
Has abstractyes

Explore more

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